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Implements MCP's tool-calling interface to allow Claude and other MCP-compatible clients to invoke searches as first-class functions within agent workflows.","intents":["I want my Claude agent to search the web for current information without building custom API integration","I need to augment my LLM's knowledge with real-time web results during reasoning tasks","I'm building a research assistant that should retrieve and cite sources from the internet"],"best_for":["AI agent developers using Claude or other MCP-compatible LLMs","Teams building research and fact-checking workflows","Developers prototyping LLM applications that need web grounding"],"limitations":["Requires valid Exa API key and active subscription; free tier may have rate limits","Search quality depends on Exa's neural ranking model; may not match traditional keyword search for niche queries","MCP protocol overhead adds ~100-200ms latency per search request compared to direct API calls","No built-in caching or result deduplication across multiple agent steps"],"requires":["Exa API key from https://exa.ai","MCP-compatible client (Claude Desktop, or custom MCP host)","Node.js 16+ (if running the MCP server locally)"],"input_types":["natural language search query (string)","optional search parameters (num_results, include_domains, exclude_domains)"],"output_types":["structured JSON with search results array","each result contains: url, title, snippet, published_date, score"],"categories":["tool-use-integration","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-exa__cap_1","uri":"capability://tool.use.integration.mcp.tool.schema.translation","name":"mcp-tool-schema-translation","description":"Translates Exa's REST API schema into MCP-compliant tool definitions, handling parameter validation, type coercion, and error mapping. The server implements MCP's tools/list and tools/call handlers, converting incoming tool invocations into properly formatted Exa API requests and marshaling responses back into MCP's structured format. Manages authentication by accepting the Exa API key as an environment variable and injecting it into all outbound requests.","intents":["I want to expose a REST API as an MCP tool without writing boilerplate schema translation code","I need my LLM to call Exa search with proper parameter validation and error handling","I'm building an MCP server and need a reference implementation for API bridging"],"best_for":["MCP server developers wrapping third-party APIs","Teams standardizing on MCP for agent tool discovery","Developers building composable tool ecosystems"],"limitations":["Schema translation is one-directional (REST → MCP); complex nested parameters may require custom mapping logic","No automatic OpenAPI/Swagger parsing; schema must be manually defined or hardcoded","Error responses from Exa API are passed through with minimal transformation; clients must handle Exa-specific error codes"],"requires":["Exa API key (set as EXA_API_KEY environment variable)","MCP client that supports tools/list and tools/call protocol methods","Node.js 16+ with npm or yarn"],"input_types":["MCP tool invocation with parameters (JSON)","Exa API key (environment variable)"],"output_types":["MCP tool result (JSON with content array)","Exa search results formatted as text/JSON content blocks"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-exa__cap_2","uri":"capability://planning.reasoning.agent.compatible.search.integration","name":"agent-compatible-search-integration","description":"Enables LLM agents (particularly Claude) to autonomously invoke web searches as part of multi-step reasoning workflows. The MCP server registers search as a callable tool that agents can discover, invoke with natural language parameters, and incorporate results into subsequent reasoning steps. Supports agent patterns like ReAct (Reasoning + Acting) where the agent decides when to search, evaluates results, and refines queries iteratively.","intents":["I want my agent to automatically search for information when it realizes its training data is insufficient","I need to build a multi-step workflow where the agent searches, analyzes results, and decides if more searches are needed","I'm implementing a fact-checking agent that retrieves sources and validates claims"],"best_for":["AI agent developers building autonomous research systems","Teams implementing ReAct or similar agent patterns","Builders creating fact-checking or verification workflows"],"limitations":["Agent search behavior is non-deterministic; same query may produce different results across runs due to Exa's ranking","No built-in loop detection; agents may enter infinite search loops if not properly constrained with max_iterations","Search results are stateless; agents cannot maintain search history across tool calls without external memory","Agents may over-rely on search for questions answerable from training data, increasing latency and API costs"],"requires":["Claude or another MCP-compatible agent framework","Exa API key with sufficient quota for agent-driven searches","MCP server running and accessible to the agent client"],"input_types":["agent reasoning state (implicit)","natural language search queries generated by the agent"],"output_types":["search results integrated into agent's context window","agent's next action (search again, analyze, respond, etc.)"],"categories":["planning-reasoning","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-exa__cap_3","uri":"capability://tool.use.integration.configurable.search.parameters.exposure","name":"configurable-search-parameters-exposure","description":"Exposes Exa's search API parameters (num_results, include_domains, exclude_domains, start_published_date, end_published_date, etc.) as MCP tool parameters, allowing callers to customize search behavior without modifying the server. Parameters are validated and passed through to Exa's API; the server handles type coercion and provides sensible defaults for optional parameters.","intents":["I want to limit search results to specific domains or time ranges","I need to exclude certain sources from search results","I want to control how many results are returned to manage token usage"],"best_for":["Developers building specialized search workflows (e.g., news-only, academic-only)","Teams optimizing token usage by controlling result volume","Builders implementing domain-specific search constraints"],"limitations":["Parameter validation is basic; complex filter logic (e.g., regex domain matching) is not supported","Date range filtering depends on Exa's indexing; very recent content may not be available","No parameter presets or saved search configurations; each invocation must specify all parameters","Parameter changes require MCP client updates; no server-side configuration file support"],"requires":["MCP client that supports passing tool parameters","Knowledge of Exa API parameter names and valid value ranges"],"input_types":["search query (string)","num_results (integer, 1-100)","include_domains (array of strings)","exclude_domains (array of strings)","start_published_date, end_published_date (ISO 8601 strings)"],"output_types":["filtered search results matching specified constraints","metadata indicating which parameters were applied"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-exa__cap_4","uri":"capability://automation.workflow.error.handling.and.api.resilience","name":"error-handling-and-api-resilience","description":"Implements error handling for Exa API failures (rate limits, invalid queries, authentication errors) and translates them into MCP-compatible error responses. The server catches HTTP errors, network timeouts, and malformed responses, returning structured error messages that agents and clients can interpret. Includes basic retry logic for transient failures (5xx errors) with exponential backoff.","intents":["I want my agent to gracefully handle search failures without crashing","I need to understand why a search failed (rate limit vs. invalid query vs. network error)","I want automatic retries for transient API failures"],"best_for":["Production agent deployments requiring reliability","Teams building fault-tolerant search workflows","Developers debugging search integration issues"],"limitations":["Retry logic is basic (fixed backoff, no jitter); may not be optimal for high-concurrency scenarios","No circuit breaker pattern; repeated failures don't trigger fallback behavior","Error messages are Exa-specific; clients must understand Exa error codes","No logging or observability hooks; errors are only visible through MCP responses"],"requires":["Exa API key with valid quota","Network connectivity to Exa's API endpoints"],"input_types":["search query","Exa API responses (success or error)"],"output_types":["MCP error response with error code and message","structured error details (error type, retry-able flag, etc.)"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":20,"verified":false,"data_access_risk":"low","permissions":["Exa API key from https://exa.ai","MCP-compatible client (Claude Desktop, or custom MCP host)","Node.js 16+ (if running the MCP server locally)","Exa API key (set as EXA_API_KEY environment variable)","MCP client that supports tools/list and tools/call protocol methods","Node.js 16+ with npm or yarn","Claude or another MCP-compatible agent framework","Exa API key with sufficient quota for agent-driven searches","MCP server running and accessible to the agent client","MCP client that supports passing tool parameters"],"failure_modes":["Requires valid Exa API key and active subscription; free tier may have rate limits","Search quality depends on Exa's neural ranking model; may not match traditional keyword search for niche queries","MCP protocol overhead adds ~100-200ms latency per search request compared to direct API calls","No built-in caching or result deduplication across multiple agent steps","Schema translation is one-directional (REST → MCP); complex nested parameters may require custom mapping logic","No automatic OpenAPI/Swagger parsing; schema must be manually defined or hardcoded","Error responses from Exa API are passed through with minimal transformation; clients must handle Exa-specific error codes","Agent search behavior is non-deterministic; same query may produce different results across runs due to Exa's ranking","No built-in loop detection; agents may enter infinite search loops if not properly constrained with max_iterations","Search results are stateless; agents cannot maintain search history across tool calls without external memory","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.2,"ecosystem":0.25,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.35,"quality":0.2,"ecosystem":0.1,"match_graph":0.3,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-06-17T09:51:03.039Z","last_scraped_at":"2026-05-03T14:00:20.516Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=exa","compare_url":"https://unfragile.ai/compare?artifact=exa"}},"signature":"UUY23012tX6Q+mtzdEZfleIXdofILg++67NmEP28OUppDMpWQxfCL/JV6KiCN6DYJrn5WgIPgJCyWmNe21oYCA==","signedAt":"2026-06-21T23:44:14.734Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/exa","artifact":"https://unfragile.ai/exa","verify":"https://unfragile.ai/api/v1/verify?slug=exa","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}